Overview

Dataset statistics

Number of variables11
Number of observations108
Missing cells87
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory93.2 B

Variable types

Categorical2
Text5
Numeric4

Alerts

우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
홈페이지주소 has 86 (79.6%) missing valuesMissing
지번주소 has unique valuesUnique
전화번호 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2024-05-03 19:00:20.357048
Analysis finished2024-05-03 19:00:27.914665
Duration7.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size996.0 B
수원시
14 
화성시
11 
안산시
9 
고양시
9 
남양주시
7 
Other values (19)
58 

Length

Max length4
Median length3
Mean length3.1111111
Min length3

Unique

Unique7 ?
Unique (%)6.5%

Sample

1st row고양시
2nd row고양시
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
수원시 14
13.0%
화성시 11
 
10.2%
안산시 9
 
8.3%
고양시 9
 
8.3%
남양주시 7
 
6.5%
성남시 7
 
6.5%
평택시 7
 
6.5%
부천시 6
 
5.6%
의정부시 5
 
4.6%
김포시 4
 
3.7%
Other values (14) 29
26.9%

Length

2024-05-03T19:00:28.161521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 14
13.0%
화성시 11
 
10.2%
안산시 9
 
8.3%
고양시 9
 
8.3%
남양주시 7
 
6.5%
성남시 7
 
6.5%
평택시 7
 
6.5%
부천시 6
 
5.6%
의정부시 5
 
4.6%
시흥시 4
 
3.7%
Other values (14) 29
26.9%

업종명
Categorical

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
의원
45 
치과의원
40 
병원
11 
한의원
10 
치과병원
 
2

Length

Max length4
Median length2
Mean length2.8703704
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의원
2nd row치과의원
3rd row치과의원
4th row치과의원
5th row치과병원

Common Values

ValueCountFrequency (%)
의원 45
41.7%
치과의원 40
37.0%
병원 11
 
10.2%
한의원 10
 
9.3%
치과병원 2
 
1.9%

Length

2024-05-03T19:00:28.663011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:00:29.073803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 45
41.7%
치과의원 40
37.0%
병원 11
 
10.2%
한의원 10
 
9.3%
치과병원 2
 
1.9%

의료시설명
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-05-03T19:00:30.229338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.6018519
Min length3

Characters and Unicode

Total characters929
Distinct characters195
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row365서울소아청소년과의원
2nd row미시간치과의원
3rd row삼송서울치과의원
4th row서울백치과의원
5th row연세플라워치과병원
ValueCountFrequency (%)
생명마루한의원 2
 
1.8%
행복한봄정형외과산부인과의원 1
 
0.9%
평촌아크로한의원 1
 
0.9%
365키즈소아청소년과의원 1
 
0.9%
중동서울정형외과의원 1
 
0.9%
에버플란트치과의원 1
 
0.9%
소아청소년과의원 1
 
0.9%
아이웰봄 1
 
0.9%
365힐링의원 1
 
0.9%
유준상가정의학과의원 1
 
0.9%
Other values (100) 100
90.1%
2024-05-03T19:00:32.463015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 109
 
11.7%
의 102
 
11.0%
과 79
 
8.5%
치 44
 
4.7%
소 38
 
4.1%
아 28
 
3.0%
이 20
 
2.2%
년 17
 
1.8%
청 17
 
1.8%
한 16
 
1.7%
Other values (185) 459
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 885
95.3%
Decimal Number 33
 
3.6%
Uppercase Letter 6
 
0.6%
Space Separator 3
 
0.3%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 109
 
12.3%
의 102
 
11.5%
과 79
 
8.9%
치 44
 
5.0%
소 38
 
4.3%
아 28
 
3.2%
이 20
 
2.3%
년 17
 
1.9%
청 17
 
1.9%
한 16
 
1.8%
Other values (173) 415
46.9%
Uppercase Letter
ValueCountFrequency (%)
Y 1
16.7%
E 1
16.7%
S 1
16.7%
O 1
16.7%
N 1
16.7%
T 1
16.7%
Decimal Number
ValueCountFrequency (%)
3 11
33.3%
5 11
33.3%
6 11
33.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
h 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 885
95.3%
Common 36
 
3.9%
Latin 8
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 109
 
12.3%
의 102
 
11.5%
과 79
 
8.9%
치 44
 
5.0%
소 38
 
4.3%
아 28
 
3.2%
이 20
 
2.3%
년 17
 
1.9%
청 17
 
1.9%
한 16
 
1.8%
Other values (173) 415
46.9%
Latin
ValueCountFrequency (%)
Y 1
12.5%
E 1
12.5%
S 1
12.5%
O 1
12.5%
N 1
12.5%
e 1
12.5%
h 1
12.5%
T 1
12.5%
Common
ValueCountFrequency (%)
3 11
30.6%
5 11
30.6%
6 11
30.6%
3
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 885
95.3%
ASCII 44
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 109
 
12.3%
의 102
 
11.5%
과 79
 
8.9%
치 44
 
5.0%
소 38
 
4.3%
아 28
 
3.2%
이 20
 
2.3%
년 17
 
1.9%
청 17
 
1.9%
한 16
 
1.8%
Other values (173) 415
46.9%
ASCII
ValueCountFrequency (%)
3 11
25.0%
5 11
25.0%
6 11
25.0%
3
 
6.8%
Y 1
 
2.3%
E 1
 
2.3%
S 1
 
2.3%
O 1
 
2.3%
N 1
 
2.3%
e 1
 
2.3%
Other values (2) 2
 
4.5%

도로명주소
Text

Distinct107
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Memory size996.0 B
2024-05-03T19:00:33.365640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length18.841121
Min length14

Characters and Unicode

Total characters2016
Distinct characters154
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 덕양구 화중로 66
2nd row경기도 고양시 덕양구 중앙로 438
3rd row경기도 고양시 덕양구 권율대로 672
4th row경기도 고양시 일산서구 일중로 46
5th row경기도 고양시 일산동구 정발산로42번길 5
ValueCountFrequency (%)
경기도 107
 
21.9%
수원시 13
 
2.7%
화성시 11
 
2.3%
안산시 9
 
1.8%
고양시 9
 
1.8%
영통구 7
 
1.4%
성남시 7
 
1.4%
평택시 7
 
1.4%
남양주시 7
 
1.4%
부천시 6
 
1.2%
Other values (232) 305
62.5%
2024-05-03T19:00:34.690578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
381
18.9%
경 112
 
5.6%
기 112
 
5.6%
시 111
 
5.5%
도 107
 
5.3%
로 104
 
5.2%
1 76
 
3.8%
2 60
 
3.0%
구 54
 
2.7%
원 32
 
1.6%
Other values (144) 867
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1273
63.1%
Space Separator 381
 
18.9%
Decimal Number 350
 
17.4%
Dash Punctuation 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 112
 
8.8%
기 112
 
8.8%
시 111
 
8.7%
도 107
 
8.4%
로 104
 
8.2%
구 54
 
4.2%
원 32
 
2.5%
양 28
 
2.2%
산 27
 
2.1%
안 25
 
2.0%
Other values (132) 561
44.1%
Decimal Number
ValueCountFrequency (%)
1 76
21.7%
2 60
17.1%
7 32
9.1%
3 32
9.1%
0 31
8.9%
4 31
8.9%
6 28
 
8.0%
8 24
 
6.9%
5 23
 
6.6%
9 13
 
3.7%
Space Separator
ValueCountFrequency (%)
381
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1273
63.1%
Common 743
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 112
 
8.8%
기 112
 
8.8%
시 111
 
8.7%
도 107
 
8.4%
로 104
 
8.2%
구 54
 
4.2%
원 32
 
2.5%
양 28
 
2.2%
산 27
 
2.1%
안 25
 
2.0%
Other values (132) 561
44.1%
Common
ValueCountFrequency (%)
381
51.3%
1 76
 
10.2%
2 60
 
8.1%
7 32
 
4.3%
3 32
 
4.3%
0 31
 
4.2%
4 31
 
4.2%
6 28
 
3.8%
8 24
 
3.2%
5 23
 
3.1%
Other values (2) 25
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1273
63.1%
ASCII 743
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
381
51.3%
1 76
 
10.2%
2 60
 
8.1%
7 32
 
4.3%
3 32
 
4.3%
0 31
 
4.2%
4 31
 
4.2%
6 28
 
3.8%
8 24
 
3.2%
5 23
 
3.1%
Other values (2) 25
 
3.4%
Hangul
ValueCountFrequency (%)
경 112
 
8.8%
기 112
 
8.8%
시 111
 
8.7%
도 107
 
8.4%
로 104
 
8.2%
구 54
 
4.2%
원 32
 
2.5%
양 28
 
2.2%
산 27
 
2.1%
안 25
 
2.0%
Other values (132) 561
44.1%

지번주소
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-05-03T19:00:35.294848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length40
Mean length32.111111
Min length19

Characters and Unicode

Total characters3468
Distinct characters223
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 덕양구 화정동 982번지 롯데마트
2nd row경기도 고양시 덕양구 행신동 1083-3번지 아름터프라자 301호
3rd row경기도 고양시 덕양구 원흥동 627번지 411호~413호
4th row경기도 고양시 일산서구 일산동 1681-1번지 3층
5th row경기도 고양시 일산동구 장항동 848번지 대한생명일산사옥 12층
ValueCountFrequency (%)
경기도 108
 
15.4%
2층 14
 
2.0%
수원시 14
 
2.0%
3층 13
 
1.9%
화성시 11
 
1.6%
안산시 9
 
1.3%
고양시 9
 
1.3%
영통구 8
 
1.1%
남양주시 7
 
1.0%
평택시 7
 
1.0%
Other values (388) 500
71.4%
2024-05-03T19:00:36.665273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
592
 
17.1%
1 131
 
3.8%
0 120
 
3.5%
2 116
 
3.3%
지 115
 
3.3%
기 113
 
3.3%
3 113
 
3.3%
동 113
 
3.3%
시 112
 
3.2%
도 110
 
3.2%
Other values (213) 1833
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1945
56.1%
Decimal Number 794
22.9%
Space Separator 592
 
17.1%
Dash Punctuation 77
 
2.2%
Other Punctuation 37
 
1.1%
Math Symbol 14
 
0.4%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 115
 
5.9%
기 113
 
5.8%
동 113
 
5.8%
시 112
 
5.8%
도 110
 
5.7%
경 108
 
5.6%
번 108
 
5.6%
호 77
 
4.0%
구 55
 
2.8%
층 50
 
2.6%
Other values (193) 984
50.6%
Decimal Number
ValueCountFrequency (%)
1 131
16.5%
0 120
15.1%
2 116
14.6%
3 113
14.2%
4 69
8.7%
5 62
7.8%
6 57
7.2%
7 48
 
6.0%
8 47
 
5.9%
9 31
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
W 1
33.3%
B 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 35
94.6%
. 2
 
5.4%
Space Separator
ValueCountFrequency (%)
592
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1945
56.1%
Common 1520
43.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 115
 
5.9%
기 113
 
5.8%
동 113
 
5.8%
시 112
 
5.8%
도 110
 
5.7%
경 108
 
5.6%
번 108
 
5.6%
호 77
 
4.0%
구 55
 
2.8%
층 50
 
2.6%
Other values (193) 984
50.6%
Common
ValueCountFrequency (%)
592
38.9%
1 131
 
8.6%
0 120
 
7.9%
2 116
 
7.6%
3 113
 
7.4%
- 77
 
5.1%
4 69
 
4.5%
5 62
 
4.1%
6 57
 
3.8%
7 48
 
3.2%
Other values (7) 135
 
8.9%
Latin
ValueCountFrequency (%)
A 1
33.3%
W 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1945
56.1%
ASCII 1523
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
592
38.9%
1 131
 
8.6%
0 120
 
7.9%
2 116
 
7.6%
3 113
 
7.4%
- 77
 
5.1%
4 69
 
4.5%
5 62
 
4.1%
6 57
 
3.7%
7 48
 
3.2%
Other values (10) 138
 
9.1%
Hangul
ValueCountFrequency (%)
지 115
 
5.9%
기 113
 
5.8%
동 113
 
5.8%
시 112
 
5.8%
도 110
 
5.7%
경 108
 
5.6%
번 108
 
5.6%
호 77
 
4.0%
구 55
 
2.8%
층 50
 
2.6%
Other values (193) 984
50.6%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14646.481
Minimum10073
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-03T19:00:37.244590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10073
5-th percentile10387.4
Q112204.75
median14915
Q316706
95-th percentile18453
Maximum18611
Range8538
Interquartile range (IQR)4501.25

Descriptive statistics

Standard deviation2692.5358
Coefficient of variation (CV)0.18383499
Kurtosis-1.1991447
Mean14646.481
Median Absolute Deviation (MAD)2165
Skewness-0.2070682
Sum1581820
Variance7249748.8
MonotonicityNot monotonic
2024-05-03T19:00:37.891134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10083 2
 
1.9%
15537 2
 
1.9%
10402 2
 
1.9%
15239 2
 
1.9%
18453 2
 
1.9%
11473 1
 
0.9%
11760 1
 
0.9%
11613 1
 
0.9%
16022 1
 
0.9%
16988 1
 
0.9%
Other values (93) 93
86.1%
ValueCountFrequency (%)
10073 1
0.9%
10083 2
1.9%
10113 1
0.9%
10340 1
0.9%
10386 1
0.9%
10390 1
0.9%
10402 2
1.9%
10403 1
0.9%
10486 1
0.9%
10500 1
0.9%
ValueCountFrequency (%)
18611 1
0.9%
18603 1
0.9%
18592 1
0.9%
18505 1
0.9%
18472 1
0.9%
18453 2
1.9%
18442 1
0.9%
18433 1
0.9%
18398 1
0.9%
18320 1
0.9%

전화번호
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-05-03T19:00:38.763696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.953704
Min length8

Characters and Unicode

Total characters1291
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st row031-975-5056
2nd row031-973-7522
3rd row02-356-2835
4th row031-977-2875
5th row031-917-4009
ValueCountFrequency (%)
031-975-5056 1
 
0.9%
031-446-2275 1
 
0.9%
031-855-7222 1
 
0.9%
031-423-5575 1
 
0.9%
031-287-0770 1
 
0.9%
031-335-7528 1
 
0.9%
031-206-1119 1
 
0.9%
031-8023-5365 1
 
0.9%
031-377-9922 1
 
0.9%
031-375-4197 1
 
0.9%
Other values (98) 98
90.7%
2024-05-03T19:00:40.096035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 213
16.5%
0 173
13.4%
3 164
12.7%
1 162
12.5%
2 127
9.8%
5 114
8.8%
7 85
 
6.6%
8 85
 
6.6%
9 71
 
5.5%
6 57
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1078
83.5%
Dash Punctuation 213
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 173
16.0%
3 164
15.2%
1 162
15.0%
2 127
11.8%
5 114
10.6%
7 85
7.9%
8 85
7.9%
9 71
6.6%
6 57
 
5.3%
4 40
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 213
16.5%
0 173
13.4%
3 164
12.7%
1 162
12.5%
2 127
9.8%
5 114
8.8%
7 85
 
6.6%
8 85
 
6.6%
9 71
 
5.5%
6 57
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 213
16.5%
0 173
13.4%
3 164
12.7%
1 162
12.5%
2 127
9.8%
5 114
8.8%
7 85
 
6.6%
8 85
 
6.6%
9 71
 
5.5%
6 57
 
4.4%

홈페이지주소
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing86
Missing (%)79.6%
Memory size996.0 B
2024-05-03T19:00:40.648427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length30
Mean length28.181818
Min length17

Characters and Unicode

Total characters620
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st rowhttp://www.flowerdent.co.kr
2nd rowhttp://www.udh.co.kr
3rd rowhttp://www.udh.co.kr
4th rowhttp://www.yemidambc.co.kr
5th rowhttp://www.hanacli.co.kr
ValueCountFrequency (%)
http://www.udh.co.kr 2
 
9.1%
http://soodental.co.kr 1
 
4.5%
http://bwhani.com 1
 
4.5%
http://www.hdream.kr/index.asp 1
 
4.5%
http://www.ohneuldo.com 1
 
4.5%
http://ssurgery.co.kr 1
 
4.5%
http://www.barunhospital.com 1
 
4.5%
www.jdseoul.co.kr 1
 
4.5%
http://www.smilelee.co.kr 1
 
4.5%
http://www.happyview.net 1
 
4.5%
Other values (11) 11
50.0%
2024-05-03T19:00:41.768275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 61
 
9.8%
. 58
 
9.4%
t 52
 
8.4%
/ 50
 
8.1%
h 41
 
6.6%
p 35
 
5.6%
o 33
 
5.3%
e 26
 
4.2%
c 25
 
4.0%
r 24
 
3.9%
Other values (28) 215
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 462
74.5%
Other Punctuation 133
 
21.5%
Decimal Number 14
 
2.3%
Math Symbol 4
 
0.6%
Connector Punctuation 4
 
0.6%
Uppercase Letter 3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 61
13.2%
t 52
11.3%
h 41
 
8.9%
p 35
 
7.6%
o 33
 
7.1%
e 26
 
5.6%
c 25
 
5.4%
r 24
 
5.2%
m 20
 
4.3%
a 19
 
4.1%
Other values (14) 126
27.3%
Other Punctuation
ValueCountFrequency (%)
. 58
43.6%
/ 50
37.6%
: 21
 
15.8%
? 2
 
1.5%
& 2
 
1.5%
Decimal Number
ValueCountFrequency (%)
0 6
42.9%
1 3
21.4%
4 3
21.4%
3 2
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
O 1
33.3%
S 1
33.3%
Math Symbol
ValueCountFrequency (%)
= 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 465
75.0%
Common 155
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 61
13.1%
t 52
11.2%
h 41
 
8.8%
p 35
 
7.5%
o 33
 
7.1%
e 26
 
5.6%
c 25
 
5.4%
r 24
 
5.2%
m 20
 
4.3%
a 19
 
4.1%
Other values (17) 129
27.7%
Common
ValueCountFrequency (%)
. 58
37.4%
/ 50
32.3%
: 21
 
13.5%
0 6
 
3.9%
= 4
 
2.6%
_ 4
 
2.6%
1 3
 
1.9%
4 3
 
1.9%
? 2
 
1.3%
& 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 61
 
9.8%
. 58
 
9.4%
t 52
 
8.4%
/ 50
 
8.1%
h 41
 
6.6%
p 35
 
5.6%
o 33
 
5.3%
e 26
 
4.2%
c 25
 
4.0%
r 24
 
3.9%
Other values (28) 215
34.7%

설립일자
Real number (ℝ)

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20098629
Minimum19851223
Maximum20230803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-03T19:00:42.492380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19851223
5-th percentile19953867
Q120058111
median20110564
Q320151013
95-th percentile20191186
Maximum20230803
Range379580
Interquartile range (IQR)92901.75

Descriptive statistics

Standard deviation73847.798
Coefficient of variation (CV)0.0036742704
Kurtosis0.41184864
Mean20098629
Median Absolute Deviation (MAD)49752
Skewness-0.68622538
Sum2.1706519 × 109
Variance5.4534972 × 109
MonotonicityNot monotonic
2024-05-03T19:00:43.297962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130425 2
 
1.9%
20121130 1
 
0.9%
20061114 1
 
0.9%
20121025 1
 
0.9%
20110104 1
 
0.9%
20140212 1
 
0.9%
20071221 1
 
0.9%
20230803 1
 
0.9%
20130712 1
 
0.9%
20191029 1
 
0.9%
Other values (97) 97
89.8%
ValueCountFrequency (%)
19851223 1
0.9%
19920618 1
0.9%
19940818 1
0.9%
19950303 1
0.9%
19950328 1
0.9%
19950502 1
0.9%
19960116 1
0.9%
19960318 1
0.9%
19970610 1
0.9%
19990106 1
0.9%
ValueCountFrequency (%)
20230803 1
0.9%
20230407 1
0.9%
20221212 1
0.9%
20210506 1
0.9%
20201119 1
0.9%
20191226 1
0.9%
20191113 1
0.9%
20191029 1
0.9%
20190927 1
0.9%
20190826 1
0.9%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.409334
Minimum36.98405
Maximum38.027991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-03T19:00:44.011229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.98405
5-th percentile37.053655
Q137.260488
median37.391198
Q337.620543
95-th percentile37.750057
Maximum38.027991
Range1.0439417
Interquartile range (IQR)0.3600555

Descriptive statistics

Standard deviation0.21754691
Coefficient of variation (CV)0.0058153108
Kurtosis-0.51897079
Mean37.409334
Median Absolute Deviation (MAD)0.14743491
Skewness0.18287608
Sum4040.2081
Variance0.047326657
MonotonicityNot monotonic
2024-05-03T19:00:44.720121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6329529662 1
 
0.9%
37.4018610427 1
 
0.9%
37.7502392304 1
 
0.9%
37.7581610682 1
 
0.9%
37.3900644112 1
 
0.9%
37.2766761223 1
 
0.9%
37.2374261431 1
 
0.9%
37.2371570406 1
 
0.9%
37.3207327754 1
 
0.9%
37.1953333545 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
36.9840497212 1
0.9%
36.9849901158 1
0.9%
36.9903562328 1
0.9%
36.9934341191 1
0.9%
37.0024308069 1
0.9%
37.0520274177 1
0.9%
37.0566776288 1
0.9%
37.1146380407 1
0.9%
37.1259624574 1
0.9%
37.131899423 1
0.9%
ValueCountFrequency (%)
38.0279914669 1
0.9%
37.818564629 1
0.9%
37.7596050827 1
0.9%
37.7581610682 1
0.9%
37.7577712009 1
0.9%
37.7502392304 1
0.9%
37.7497190283 1
0.9%
37.7349377432 1
0.9%
37.7253778196 1
0.9%
37.713800116 1
0.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.9771
Minimum126.66651
Maximum127.45036
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-03T19:00:45.274651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66651
5-th percentile126.74572
Q1126.82717
median127.01916
Q3127.08321
95-th percentile127.22683
Maximum127.45036
Range0.78384553
Interquartile range (IQR)0.25604635

Descriptive statistics

Standard deviation0.16458251
Coefficient of variation (CV)0.001296159
Kurtosis-0.28821652
Mean126.9771
Median Absolute Deviation (MAD)0.12167554
Skewness0.17797944
Sum13713.527
Variance0.027087403
MonotonicityNot monotonic
2024-05-03T19:00:45.847247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8311167607 1
 
0.9%
126.9529861539 1
 
0.9%
127.0605740737 1
 
0.9%
127.0368343443 1
 
0.9%
126.9774165184 1
 
0.9%
127.144117293 1
 
0.9%
127.2090038363 1
 
0.9%
127.0727131477 1
 
0.9%
127.1142600311 1
 
0.9%
127.0302328392 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
126.666513227 1
0.9%
126.6683606272 1
0.9%
126.6833513683 1
0.9%
126.7318710043 1
0.9%
126.7375690254 1
0.9%
126.7441037261 1
0.9%
126.7487166933 1
0.9%
126.752605722 1
0.9%
126.7528577007 1
0.9%
126.7599451881 1
0.9%
ValueCountFrequency (%)
127.4503587588 1
0.9%
127.4457533047 1
0.9%
127.2441133261 1
0.9%
127.243081951 1
0.9%
127.2370709113 1
0.9%
127.2347259018 1
0.9%
127.2121653871 1
0.9%
127.2090038363 1
0.9%
127.1646753745 1
0.9%
127.1632474688 1
0.9%

Interactions

2024-05-03T19:00:25.107472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:21.616965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:22.599260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:23.765876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:25.402385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:21.858060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:22.859399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:24.040033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:25.685706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:22.109097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:23.192178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:24.341291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:25.945367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:22.343941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:23.470113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:00:24.606509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:00:46.188205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업종명우편번호홈페이지주소설립일자WGS84위도WGS84경도
시군명1.0000.0000.9921.0000.3270.9720.938
업종명0.0001.0000.2181.0000.0000.1260.000
우편번호0.9920.2181.0001.0000.1310.8730.810
홈페이지주소1.0001.0001.0001.0000.9181.0000.000
설립일자0.3270.0000.1310.9181.0000.0000.271
WGS84위도0.9720.1260.8731.0000.0001.0000.704
WGS84경도0.9380.0000.8100.0000.2710.7041.000
2024-05-03T19:00:46.611441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명시군명
업종명1.0000.000
시군명0.0001.000
2024-05-03T19:00:47.039699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호설립일자WGS84위도WGS84경도시군명업종명
우편번호1.0000.058-0.9450.2940.8780.088
설립일자0.0581.000-0.0070.1510.0420.000
WGS84위도-0.945-0.0071.000-0.2440.7770.066
WGS84경도0.2940.151-0.2441.0000.6670.000
시군명0.8780.0420.7770.6671.0000.000
업종명0.0880.0000.0660.0000.0001.000

Missing values

2024-05-03T19:00:26.373585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:00:27.262318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-03T19:00:27.740972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명업종명의료시설명도로명주소지번주소우편번호전화번호홈페이지주소설립일자WGS84위도WGS84경도
0고양시의원365서울소아청소년과의원경기도 고양시 덕양구 화중로 66경기도 고양시 덕양구 화정동 982번지 롯데마트10500031-975-5056<NA>2012113037.632953126.831117
1고양시치과의원미시간치과의원경기도 고양시 덕양구 중앙로 438경기도 고양시 덕양구 행신동 1083-3번지 아름터프라자 301호10486031-973-7522<NA>2009040337.618006126.846729
2고양시치과의원삼송서울치과의원경기도 고양시 덕양구 권율대로 672경기도 고양시 덕양구 원흥동 627번지 411호~413호1056402-356-2835<NA>2013050637.649873126.874178
3고양시치과의원서울백치과의원경기도 고양시 일산서구 일중로 46경기도 고양시 일산서구 일산동 1681-1번지 3층10340031-977-2875<NA>1997061037.68363126.775374
4고양시치과병원연세플라워치과병원경기도 고양시 일산동구 정발산로42번길 5경기도 고양시 일산동구 장항동 848번지 대한생명일산사옥 12층10403031-917-4009http://www.flowerdent.co.kr2009110437.657087126.774136
5고양시치과의원유디치과의원경기도 고양시 일산동구 중앙로1261번길 19경기도 고양시 일산동구 장항동 857번지10402031-932-1110http://www.udh.co.kr2005091337.658259126.772662
6고양시의원일산우리들소아청소년과의원경기도 고양시 일산서구 중앙로 1426경기도 고양시 일산서구 주엽동 66-1번지 일송노블레스 207호, 208(일부)호, 810호10386031-916-9999<NA>2007092837.67027126.761942
7고양시한의원정성미한의원경기도 고양시 일산동구 정발산로 43-20경기도 고양시 일산동구 장항동 846번지 센트럴프라자 412~416호10402031-915-8288<NA>2004060837.65838126.773375
8고양시치과의원참플란트치과의원경기도 고양시 일산서구 킨텍스로 171경기도 고양시 일산서구 대화동 2703번지 일산 킨텍스 복합개발 지하3층 일부호10390031-915-2804http://www.udh.co.kr2015061237.661567126.744104
9과천시의원과천예일의원경기도 과천시 별양상가1로 30경기도 과천시 별양동 1-8번지 골든타워 404호~405호, 402호~403호 일부1383702-507-7582<NA>2003013037.428271126.993336
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